Retail Sales Data

This is high level summary of weekly sales data for Fiscal week 2022-01-01- 2022-01-07

library(readr)
setwd("/Users/yasmeenkhalifa/Desktop/MSQM FALL 24/R PROGRAMMING/mydata")
retail_sales <- read_csv("Retail_sales.csv")
## Rows: 30000 Columns: 11
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr  (5): Store ID, Product ID, Store Location, Product Category, Day of the...
## dbl  (4): Units Sold, Sales Revenue (USD), Discount Percentage, Marketing Sp...
## lgl  (1): Holiday Effect
## date (1): Date
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
retail_sales
## # A tibble: 30,000 × 11
##    `Store ID` `Product ID` Date       `Units Sold` `Sales Revenue (USD)`
##    <chr>      <chr>        <date>            <dbl>                 <dbl>
##  1 Spearsland 52372247     2022-01-01            9                 2742.
##  2 Spearsland 52372247     2022-01-02            7                 2666.
##  3 Spearsland 52372247     2022-01-03            1                  381.
##  4 Spearsland 52372247     2022-01-04            4                 1523.
##  5 Spearsland 52372247     2022-01-05            2                  762.
##  6 Spearsland 52372247     2022-01-06            8                 3046.
##  7 Spearsland 52372247     2022-01-07            6                 2285.
##  8 Spearsland 52372247     2022-01-08            9                 3427.
##  9 Spearsland 52372247     2022-01-09            7                 2666.
## 10 Spearsland 52372247     2022-01-10            1                  381.
## # ℹ 29,990 more rows
## # ℹ 6 more variables: `Discount Percentage` <dbl>,
## #   `Marketing Spend (USD)` <dbl>, `Store Location` <chr>,
## #   `Product Category` <chr>, `Day of the Week` <chr>, `Holiday Effect` <lgl>
mean(retail_sales$`Sales Revenue (USD)`, Date=(2022-01-01 - 2022-01-07))
## [1] 2749.51
median(retail_sales$`Sales Revenue (USD)`, Date=(2022-01-01 - 2022-01-07))
## [1] 1902.42
range(retail_sales$`Sales Revenue (USD)`, Date=(2022-01-01 - 2022-01-07))
## [1]   -10.00 27165.88